APOE_finemapping
Brian M. Schilder
Most recent update:
2021-03-19
knitr::opts_chunk$set(echo = T, root.dir="~/Desktop/APOE_finemapping")
knitr::opts_knit$set(root.dir="~/Desktop/APOE_finemapping")
library(dplyr)
library(ggplot2)
library(echolocatoR)Import fine-mapping results
Query fine-mapping portal
Download Alzheimer’s Disease GWAS fine-mapping results for the APOE locus via the echolocatoR Fine-mapping Portal API.
local_finemap <- echolocatoR::GITHUB.portal_query(dataset_types = "GWAS",
phenotypes = "Alzheimer",
LD_panels = c("UKB", "1KGphase3"),
loci = "APOE",
file_types = "multi_finemap",
results_dir = "./data",
overwrite = F)## [1] "Fetching echolocatoR Fine-mapping Portal study metadata."
## [1] "+ 4 datasets remain after filtering."
## [1] "+ Searching for multi_finemap files..."
## [1] "+ 2 unique files identified."
## [1] "+ Downloading 2 files..."
## [1] "+ Returning local file paths."Merge fine-mapping results
finemap_dat <- lapply(local_finemap,function(x){
dataset <- basename(dirname(dirname(dirname(x))))
LD_ref <- stringr::str_split(basename(x),pattern = "[.]")[[1]][2]
printer("Importing",dataset)
dat <- data.table::fread(x)
cbind(dataset=dataset,
LD_ref=LD_ref,
dat)
}) %>% data.table::rbindlist()## [1] "Importing Jansen_2018"
## [1] "Importing Marioni_2018"Identify credible sets
Show just the Union Credible Set SNPs (SNPs nominated by at least 1/4 fine-mapping tools).
ucs_snps <- subset(finemap_dat, Support>0)
createDT(ucs_snps)Identify Consensus SNPs
Filter to just the consensus SNPs (SNPs nominated by 2 or more fine-mapping tools).
consensus_snps <- subset(finemap_dat, Consensus_SNP==T)
createDT(consensus_snps)Cell-type-specific annotations
Epigenomic peak overlap
finemap_dat$Gene<- finemap_dat$Locus
finemap_dat$Locus <- paste(finemap_dat$Locus,finemap_dat$dataset,sep="_")
plot_res <- echolocatoR::SUMMARISE.peak_overlap_plot(merged_DT = finemap_dat,
snp_filter = "Support>0",
include.NOTT_2019_peaks = T,
include.NOTT_2019_enhancers_promoters = T,
include.NOTT_2019_PLACseq = T,
include.CORCES_2020_scATACpeaks = T,
include.CORCES_2020_Cicero_coaccess = T,
include.CORCES_2020_bulkATACpeaks = T,
include.CORCES_2020_HiChIP_FitHiChIP_coaccess = T,
include.CORCES_2020_gene_annotations = T,
plot_celltype_specificity = T,
plot_celltype_specificity_genes = T)## [1] "++ NOTT_2019:: Downloading and merging 12 peaks BED files."
## [1] "++ NOTT_2019:: Converting merged BED files to GRanges."
## [1] "++ NOTT_2019:: 634540 ranges retrieved."
## [1] "Importing Astrocyte enhancers ..."
## [1] "Importing Astrocyte promoters ..."
## [1] "Importing Neuronal enhancers ..."
## [1] "Importing Neuronal promoters ..."
## [1] "Importing Oligo enhancers ..."
## [1] "Importing Oligo promoters ..."
## [1] "Importing Microglia enhancers ..."
## [1] "Importing Microglia promoters ..."
## [1] "++ Converting to GRanges."
## [1] "Importing Microglia interactome ..."
## [1] "Importing Neuronal interactome ..."
## [1] "Importing Oligo interactome ..."
## [1] "CORCES_2020:: Extracting overlapping cell-type-specific scATAC-seq peaks"
## Error in `[[<-`(`*tmp*`, name, value = "scATAC") :
## 1 elements in value to replace 0 elements
## [1] "CORCES_2020:: Extracting overlapping bulkATAC-seq peaks from brain tissue"
## Error in `[[<-`(`*tmp*`, name, value = "bulkATAC") :
## 1 elements in value to replace 0 elements
Show the epigenomic overlap results
createDT(plot_res$data)Summarise assay counts
Summarise the number of assays in which at least one UCS SNP overlapped with a cell-type-specific epigenomic peak.
celltype_counts <- plot_res$data %>%
dplyr::group_by(Locus, Cell_type) %>%
dplyr::summarise(Count=sum(Count,na.rm = T)) %>%
dplyr::arrange(Locus, desc(Count))## `summarise()` has grouped output by 'Locus'. You can override using the `.groups` argument.createDT(celltype_counts)Session info
sessioninfo::session_info()## ─ Session info ───────────────────────────────────────────────────────────────
## setting value
## version R version 4.0.4 (2021-02-15)
## os macOS Big Sur 10.16
## system x86_64, darwin17.0
## ui X11
## language (EN)
## collate en_GB.UTF-8
## ctype en_GB.UTF-8
## tz Europe/London
## date 2021-03-19
##
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